Between 1990 and 1998 the prevalence of diabetes in the United States rose from 4.9 to 6.5%. During the 1990's the prevalence of non-insulin dependent diabetes increased by 33% overall and by 70% among people in their thirties. Diabetes affects now sixteen million Americans. The direct costs resulting from diabetes is $44 billion per year, and the total cost of diabetes, including indirect costs, rises to $98 billion per year. 13.5% of obese patients have diabetes compared to 3.5% of those with a normal weight.
Diabetes is the “tip of the Iceberg” and is most often preceded by a metabolic syndrome. The prevalence of the metabolic syndrome gives an estimate of the potential magnitude of the problem. The Centers of Disease Control and Prevention recently investigated the prevalence of the metabolic syndrome: The unadjusted and age-adjusted prevalences were 21.8% and 23.7%, respectively. The prevalence increased from 6.7% among participants aged 20 through 29 years to 43.5% and 42.0% for participants aged 60 through 69 years and aged at least 70 years, respectively. Using 2000 census data, about 47 million US residents have the metabolic syndrome.
Most patients who go through the evolution of metabolic syndrome to diabetes will ultimately require insulin injections to deal with their disease. According to research, the well educated Type I diabetes patient encounters on average about 5 hypoglycaemic episodes and about the same hyperglycaemic episodes every week. Both conditions may lead to a variety of complications, such as lack in concentration, loss of conscience, coma, dehydration and death.
A major draw back of the algorithms used to predict glucose levels in the prior art is that the algorithms use theoretical absorption curves of the injected insulin. These curves try to predict the appearance of insulin in the bloodstream and the insulin activity which is then used in the prediction model. The current prediction algorithms do not take into account other insulin-interfering factors, and are therefore often highly inaccurate.